Multimodal Prognostic System for Heart Failure: A Multi-Center Study

NCT06558448 | Not Yet Recruiting

• 1 other identifier: CYS240347
• Study Type: observational
• Target: 100,000
• Locations: 0 countries
• Sites: N/A

Brief Summary

This study is a multicenter retrospective research aimed at developing a heart failure prognosis warning system based on multimodal clinical data to improve the diagnosis and treatment of heart failure. This study aims to address the following main questions:

1. 1.What are the clinical characteristics and current treatment status of heart failure patients?
2. 2.What factors influence the onset of heart failure and the prognosis of patients?
3. 3.How can real-world big data be utilized to construct an accurate heart failure prognosis assessment model?
4. 4.How can this prognosis assessment model help improve the therapeutic effects and quality of life for heart failure patients?

Conditions

Heart Failure

Outcome Measures

Primary Outcomes (1)

• In-hospital mortality or other adverse outcomes, including readmission, in-hospital infection, respiratory failure, liver failure, and renal failure.

  The study focuses on evaluating the risk factors and predictors of in-hospital mortality and various adverse outcomes in heart failure patients, encompassing events such as readmission due to exacerbation of the condition, infections acquired during hospital stay, critical impairments in respiratory, liver, and kidney functions that may complicate the clinical course and impact patient prognosis.

  Evaluations will be conducted within 30, 60, or 90 days post-admission for heart failure patients to assess the impact of the condition and the effectiveness of treatment.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population for this research consists of adult patients, aged 18 and above, with a discharge diagnosis of heart failure between January 2011 and December 2024, as per the guidelines for the diagnosis and treatment of heart failure . The patients' electronic medical records, which include demographic information, comorbidities, treatment plans, and various clinical indicators, are sourced , ensuring a comprehensive and in-depth analysis of the heart failure patient cohort.

You may qualify if:

• Age Requirement: We plan to include adult patients aged 18 and above to ensure the study covers a broad spectrum of the adult heart failure patient population.
• Diagnostic Criteria: Patients should have a discharge diagnosis of heart failure according to the guidelines for heart failure diagnosis and treatment.
• Time Frame: The discharge time of patients should be between January 2011 and December 2024 to collect and analyze data from the past several years.
• Data Integrity: There is a preference for including medical records with high data integrity, but the specific criteria may be adjusted according to the actual situation of the dataset.

You may not qualify if:

• Diagnostic Inconsistency: Patients with unclear diagnoses or potential for confusion with other diseases may be excluded to ensure the specificity of the study.
• Non-standard Treatment: Patients who have not received treatment according to the established treatment protocol may be excluded to reduce the impact of treatment variability on the study results.

Sponsors & Collaborators

• Chongqing Medical University: lead

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: student

Study Record Dates

• First Submitted: August 14, 2024
• First Posted: August 16, 2024
• Study Start: August 1, 2024
• Primary Completion: December 1, 2024
• Study Completion: December 1, 2024
• Last Updated: August 16, 2024

Record last verified: 2024-08

Data Sharing

• IPD Sharing: Will not share